JOB DESCRIPTION
Make an impact with NTT DATA
Join a company that is pushing the boundaries of what is possible. We are renowned for our technical excellence and leading innovations, and for making a difference to our clients and society. Our workplace embraces diversity and inclusion – it’s a place where you can grow, belong and thrive.
Role Purpose
Drive technical excellence and customer engagement for NTT Data's AI Factories initiative by developing innovative AI solutions, maintaining the Munich demonstrator lab, supporting pre-sales activities, and creating thought leadership content. This role bridges the gap between AI/ML capabilities and business value, ensuring NTT Data showcases world-class AI implementations to win €2.2B in European market opportunities.
Strategic Context
This position is critical for demonstrating NTT Data's AI capabilities to EuroHPC evaluators and enterprise customers. The role directly supports the Munich AI Experience Centre (€3.5M investment) and enables customer proof-of-concepts that convert to €35M+ deals.
Core Responsibilities
1. AI Experience Centre Operations (30%)
Lab Infrastructure Management
1. Maintain and optimize the Munich AI Factory lab environment:
2. NVIDIA H200 GPUs + 16x AMD MI300X GPUs
3. Kubernetes orchestration with multi-tenant isolation
4. MLOps pipeline with MLflow, Kubeflow, Ray
5. 2 PB storage with parallel filesystem
6. Ensure 99.9% lab availability for customer demonstrations
7. Implement automated provisioning for rapid PoC deployment
8. Manage software stack updates (PyTorch, TensorFlow, JAX)
Platform Excellence
9. Deploy and maintain AI platforms:
10. NVIDIA AI Enterprise suite
11. Mistral AI European LLM integration
12. Container orchestration with GPU operators
13. Multi-cloud management capabilities
14. Optimize resource utilization across workloads
15. Implement cost tracking and chargeback mechanisms
16. Maintain security compliance (GDPR, ISO 27001)
2. Use Case Development & Innovation (25%)
Industry Solution Development
Create reusable AI solutions by vertical:
Financial Services
17. Fraud detection systems (real-time inference <10ms)
18. Risk modeling with explainable AI
19. Regulatory compliance automation (MiFID II, Basel III)
20. Synthetic data generation for testing
Manufacturing
21. Predictive maintenance with IoT integration
22. Quality inspection using computer vision
23. Digital twin simulations
24. Supply chain optimization
Healthcare
25. Medical imaging analysis (DICOM integration)
26. Drug discovery acceleration
27. Patient outcome prediction
28. Privacy-preserving federated learning
Public Sector
29. Climate modeling and simulation
30. Smart city applications
31. Document intelligence for government
32. Citizen service automation
Technical Innovation
33. Develop cutting-edge demonstrations:
34. Large Language Model fine-tuning (7B-70B parameters)
35. Multi-modal AI (vision + language)
36. Reinforcement learning for optimization
37. Edge-to-cloud AI deployment
38. Create benchmarking frameworks
39. Implement MLOps best practices
40. Build reusable solution accelerators
3. Pre-Sales Technical Support (20%)
Customer Demonstrations
41. Execute compelling AI demonstrations:
42. Live model training on customer data
43. Performance benchmarking (MLPerf results)
44. Scaling demonstrations (1 to 100+ GPUs)
45. ROI calculations and business case
46. Customize demos for specific industries
47. Handle technical Q&A during presentations
48. Troubleshoot issues in real-time
Proof of Concept Delivery
49. Design and execute customer PoCs:
50. 2-4 week sprint engagements
51. Success criteria definition
52. Performance validation
53. Knowledge transfer to customer teams
54. Document results and recommendations
55. Support proposal development with technical content
56. Provide effort estimates for implementations
4. Thought Leadership & Content Creation (15%)
Technical Content Development
57. Produce high-quality technical content:Whitepapers on AI implementation strategiesSolution briefs for industry use casesTechnical blogs and articlesReference architecture documentation
58. Create customer-facing materials:Demo scripts and videosWorkshop materialsTraining contentBest practice guides
Market Positioning
59. Contribute to NTT Data's AI thought leadership:
60. Conference presentations
61. Webinar delivery
62. Industry analyst briefings
63. Open-source contributions
64. Collaborate with marketing on campaigns
65. Support PR initiatives with technical expertise
66. Engage with AI community and forums
5. Technical Operations Excellence (10%)
Infrastructure Automation
67. Implement Infrastructure as Code:
68. Terraform for resource provisioning
69. Ansible for configuration management
70. GitOps for deployment automation
71. Helm charts for application packaging
72. Design CI/CD pipelines:
73. Automated model training workflows
74. A/B testing frameworks
75. Continuous monitoring and alerting
76. Automated rollback mechanisms
Monitoring & Optimization
77. Deploy comprehensive monitoring:
78. Model performance metrics
79. Infrastructure utilization
80. Cost optimization tracking
81. Security compliance monitoring
82. Implement observability stack:
83. Prometheus + Grafana dashboards
84. ELK stack for log analysis
85. Distributed tracing
86. Custom alerting rules
Required Qualifications
Education
87. Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or related field
88. AI/ML certifications highly valued
Technical Skills
Core AI/ML Expertise
89. Deep learning frameworks: PyTorch, TensorFlow, JAX
90. ML platforms: MLflow, Kubeflow, Ray, Weights & Biases
91. Model optimization: Quantization, pruning, distillation
92. Distributed training: Horovod, DeepSpeed, FairScale
Infrastructure & DevOps
93. Container orchestration: Kubernetes, Docker, Singularity
94. GPU management: NVIDIA DCGM, GPU Operator
95. Cloud platforms: Experience with sovereign European clouds preferred
96. Automation: Python, Bash, Terraform, Ansible
Data Engineering
97. Big data tools: Spark, Dask, Rapids
98. Feature stores: Feast, Tecton
99. Data versioning: DVC, Pachyderm
100. Streaming: Kafka, Pulsar
Experience Requirements
101. 3-5 years in ML engineering, MLOps, or AI solution development
102. Proven track record of production ML deployments
103. Experience with GPU-accelerated computing
104. Customer-facing technical presentation experience
105. European market knowledge preferred
Preferred Qualifications
Certifications
106. NVIDIA DLI certifications
107. Cloud ML certifications (AWS, Azure, GCP)
108. Kubernetes certifications (CKA, CKAD)
109. European data privacy certifications
Domain Expertise
110. Experience with European AI regulations (EU AI Act)
111. Knowledge of EuroHPC ecosystem
112. Familiarity with sovereign cloud requirements
113. Industry-specific AI applications
Soft Skills
114. Excellent presentation and communication abilities
115. Strong problem-solving and debugging skills
116. Ability to translate technical concepts to business value
117. Collaborative mindset for cross-functional teams
118. Entrepreneurial spirit and innovation drive
Success Metrics
Technical Excellence
119. 95%+ lab uptime and availability
120. 50+ use cases developed annually
121. 90%+ PoC success rate
122. <24 hour turnaround for demo requests
Business Impact
123. Support €100M+ pipeline through demonstrations
124. 80% PoC-to-deal conversion rate
125. 10+ whitepapers published annually
126. 5+ conference presentations per year
Innovation Metrics
127. 3+ new solution accelerators quarterly
128. 20+ reusable demonstrations maintained
129. 100+ lab tours conducted annually
130. 5-star customer feedback rating
What Makes This Role Unique
This isn't a typical MLOps role focused on production stability. This is about being the technical face of NTT Data's AI Factories initiative, where you'll:
131. Shape the Market: Your demonstrations will directly influence €50M+ procurement decisions
132. Work with Cutting-Edge Tech: Access to the latest GPUs (H200, MI300X, B300) before general availability
133. Drive Innovation: Freedom to experiment with emerging AI technologies and approaches
134. Impact at Scale: Your work will enable thousands of European organizations to adopt AI
135. Build the Future: Help establish Europe's sovereign AI infrastructure
Workplace type:
Remote Working
About NTT DATA
NTT DATA is a $30+ billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate, optimize and transform for long-term success. We invest over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. As a Global Top Employer, we have diverse experts in more than 50 countries and a robust partner ecosystem of established and start-up companies. Our services include business and technology consulting, data and artificial intelligence, industry solutions, as well as the development, implementation and management of applications, infrastructure, and connectivity. We are also one of the leading providers of digital and AI infrastructure in the world. NTT DATA is part of NTT Group and headquartered in Tokyo.
Equal Opportunity Employer
NTT DATA is proud to be an Equal Opportunity Employer with a global culture that embraces diversity. We are committed to providing an environment free of unfair discrimination and harassment. We do not discriminate based on age, race, colour, gender, sexual orientation, religion, nationality, disability, pregnancy, marital status, veteran status, or any other protected category. Join our growing global team and accelerate your career with us. Apply today.
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